Individualized Assignments and Assessment through Automated Grading

Authors: David Augenblick, Mark Boady, Bruce Char, Jeremy Johnson
Department of Computer Science
Presented at: ECADD 2011

Abstract
We have used an on-line automatic grading system, Maple TA, in a course on technical computing with over 900 freshman engineering students. Students spend ten hours per term in labs with face-to-face contact with instructional staff. On-line pre-lab quizzes guide student lab preparation. Post-lab on-line assignments provide further practice, solidifying skills. Symbolic computation generates a unique auto-gradable version of the problem sets for each student. Allowing multiple attempts per quiz encourages students to continue work until they know they have solved the problem. Peer-led and staff tutoring (face-to-face and on-line) provides "just in time" help for post-lab quizzes.
On-line storage of all test results facilitates the collection of statistics on all regularly graded materials. These can be used to identify class-wide and individual strengths and weaknesses, as well as longitudinal information on learning patterns and retention.
IT expertise is needed to keep services running with high availability and reliability. Software engineering discipline is needed to construct robust questions and grading procedures. Current limitations of auto-grading technology present pedagogical challenges.
What began as a necessity has become an essential learning tool, providing students with a learning tool that has 24/7 availability, gives immediate feedback, and is scalable.

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